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8 November 2010 SST Science Team Meeting 1
Towards Community ConsensusSSTs and Clear-Sky Radiances
from AVHRR
SST Science Team Meeting8-10 November 2010, Seattle WA
Sasha Ignatov
NOAA/NESDIS
Prasanjit Dash, Xingming Liang, Feng Xu
NOAA/NESDIS and CSU/CIRA
8 November 2010 SST Science Team Meeting 2
Contributions
AVHRR Level 2/3 SST products - J. Sapper, Y. Kihai, B. Petrenko, J. Stroup: ACSPO (GAC: 5 platforms, FRAC: MetOp-A)
- P. LeBorgne: O&SI SAF MetOp-A FRAC
- D. May, B. McKenzie: NAVO SEATEMP
- K. Casey, T. Brandon, R. Evans, J. Vazquez, E. Armstrong: PathFinder v5.0
Level 4 SST products (additional L4 SSTs are being tested)- R. Grumbine, Xu Li, B. Katz: RTG (Low-Res & Hi-Res), GSI
- R. Reynolds: OISST (AVHRR & AVHRR+AMSRE)
- M. Martin: OSTIA foundation, GHRSST Median Product Ensemble
- D. May, B. McKenzie: NAVO K10
- E. Autret, J.-F. Piollé: ODYSSEA
- E. Maturi, A. Harris, W. Meng: POES-GOES blended
- B. Brasnett: Canadian Met. Centre, 0.2 foundation
AVHRR Radiances- C. Cao, X. Wu, J. Mittaz, A. Harris, A. Heidinger, L. Wang: AVHRR Cal
- C. Cao, T. Hewison, M. König: GSICS (Global Space-based Inter-Cal System)
- Y. Han, M. Liu, Y. Chen, P. Van Delst, D. Groff, F. Weng: CRTM
8 November 2010 SST Science Team Meeting 3
SST data come from various sources, sensors, and processing algorithms
L4 Reynolds (AVHRR; +AMSR-E) RTG (Low, High Resolution), GSI OSTIA (UKMO) ODYSSEA (France) GMPE (GHRSST) NAVO K10 NESDIS POES-GOES Blended JPL G1SST CMC 0.2 (Canada) GAMSSA (Australia) JAXA (Japan) RSS (MW, MW+MODIS)
In situ Sources-GTS, ICOADS, GODAE/FNMOC
Platforms-Drifters, Moorings, Ships, ARGO Floats
Quality Control-May be unavailable or non-uniform
L2/L3 POES-AVHRR (NESDIS, NAVO, O&SI SAF, U. Miami, NODC)-MODIS, ATSR, VIIRS, ..-Microwave
GOES-GOES (NESDIS, NAVO, O&SI SAF)-SEVIRI (NESDIS, O&SI SAF)-MTSAT (NESDIS, JAXA)
Are these products self-consistent?Cross-consistent? Processed using community consensus algorithms?
8 November 2010 SST Science Team Meeting 4
Initial Focus: AVHRR
Past: Climate Data Record- Pathfinder Ocean: 1981-present
Present: Initial Joint Polar System (IJPS)- NOAA/EUMETSAT Cooperation
- NOAA: GAC (4km), NOAA-18 & -19 (2 pm/am)
(NOAA-16 and -17 are also in orbit but degraded)
- EUMETSAT: FRAC (1km) 3 mid-morning birds (9:30 am/pm)
Metop-A (19 Oct 2006), -B (2012), -C (2016)
Future: Joint Polar Satellite System (JPSS)- Europe: AVHRR/3 onboard Metop-B (~2012) & -C (2016)
- AVHRR will serve the data through at least 2021
- USA: Visible and IR Imagers Suite (VIIRS) on NPP & NPOESS- Need to ensure VIIRS/AVHRR synergy
8 November 2010 SST Science Team Meeting 5
Operational POES SST at NESDIS
Heritage Main Unit Task (MUT)- 1981 - pr (MCSST - McClain et al., 1985; NLSST - Walton et al., 1998)
- 1993 - pr: Re-hosted to NAVO (“Shared Processing Agreement”).
Robust end-to-end system. No fundamental redesign since 1981: Data sub-sampling (e.g. 2×2); No RTM; No reprocessing capability.
New Advanced Clear-Sky Processor for Oceans (ACSPO)- Development started in late 2005 (IJPS) - Operational in May 2008
Process all AVHRR pixels (GAC, FRAC). RTM & Reprocessing capability.
Joint Polar Satellite System (JPSS) - Generate AVHRR-like ACSPO products from VIIRS radiances.
Fall-back for NPOESS SST. Benchmark to measure VIIRS improvements. Smooth transition for SST users.
- Cross-evaluate against VIIRS SST generated by NPOESS contractor.
Contractor’s cloud mask + VIIRS instrument + Heritage NLSST algorithm
8 November 2010 SST Science Team Meeting 6
GAC ~4kmGlobal Area Coverage
GAC ~4kmGlobal Area Coverage
NESDIS ACSPO (new); MUT (heritage)
NESDIS ACSPO (new); MUT (heritage)
MetOp FRAC ~1kmFull Resolution Area Coverage
MetOp FRAC ~1kmFull Resolution Area Coverage
EUMETSATO&SI SAF
EUMETSATO&SI SAF
NAVOSEATEMPNAVO
SEATEMPU. Miami + NODC Pathfinder Ocean (L3)
U. Miami + NODC Pathfinder Ocean (L3)
NESDISACSPO (new)NESDIS
ACSPO (new)
Cross-evaluate ACSPO against heritage MUT SST
Current AVHRR SST Products
.. and against other available L2 AVHRR SST products
L2 vs. in situ
Customary Validation
78 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 8
Global Mean “SAT – In Situ” Global Std Dev “SAT – In Situ”
Outliers in in situ data:Critically affect validation statistics
MUT SST versus in situ SST(no QC applied to in situ SST)
8 November 2010 SST Science Team Meeting 9
Global Mean “SAT – In Situ” Global Std Dev “SAT – In Situ”
MUT SST versus in situ SST(after QC of match-up data)
QC improves both moments (Mean, Std Dev).
Most dramatically, it affects the Std Dev. Absolute values are sensitive to QC.
8 November 2010 SST Science Team Meeting 10
QC & Monitoring of in situ SST:Need community consensus
GHRSST coordinates efforts towards community consensus - Quality Control of in situ SST
- Match-up procedures and practices
NESDIS contribution- Implement in situ QC consistent with the UK Met Office
- Set up near-real time web-based in situ SST Quality Monitor (iQuam) http://www.star.nesdis.noaa.gov/sod/sst/iquam/
- Monitor QC’ed data against global L4 SST (currently, daily Reynolds)
- Serve QC’ed in situ data to SST community, in near-real time
Work in progress- Validate L2/3/4 products against in situ SSTs, using consistent QC
and match-up procedures
- Evaluate match-up criteria and iQuam QC through sensitivity studies; Adjust as needed; Seek community consensus
- Add ARGO floats to iQuam
8 November 2010 SST Science Team Meeting 11
iQuam webpage http://www.star.nesdis.noaa.gov/sod/sst/iquam/
L2/3 vs. L4
Validation against global L4
128 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 13
Validation against global L4 SSTswas first considered because…
…in situ SSTs have limitations
Non-uniform / Suboptimal quality (may be worse than satellite
SSTs)
Sparse, geographically biased, and do not cover retrieval domain,
fully and uniformly
Not available in sufficient numbers in near-real time (limited
statistics). Diagnostics delayedUsing L4 products provides global snapshot (map) of TSAT
performance, in near-real time, with uniform global coverage.
Also, QC & smoothing done at L4 production stage. Errors of
L4 SST are more uniform in space & time than for in situ data.
8 November 2010 SST Science Team Meeting 14
ΔTS=TSAT - TREF are mapped to identify issues in data, in near-real time (e.g., cold biases likely due to residual cloud)
http://www.star.nesdis.noaa.gov/sod/sst/squam/
8 November 2010 SST Science Team Meeting 15
NIGHT
DAY
NIGHT
DAY
O&SI SAF SST minus OSTIAMetop-A FRAC 16-Oct-2010
8 November 2010 SST Science Team Meeting 16
NIGHT
DAY
NIGHT
DAY
NESDIS ACSPO SST minus OSTIAMetop-A FRAC 16-Oct-2010
8 November 2010 SST Science Team Meeting 17
NIGHT NIGHT NIGHT
DAY DAYDAY
O&SI SAF: ~40 M clear pixels/night and ~40 M/day.
At night, ACSPO produces ~15% clear-sky ocean pixels than O&SI SAF. Global median biases and Robust Std Dev (RSD) wrt. OSTIA are comparable.
During daytime, # of clear-sky ocean pixels comparable in ACSPO and O&SI. Global median biases: comparable; RSD: slightly smaller for ACSPO.
O&SI SAF ACSPO
O&SI SAF ACSPON
um
ber
of
Ob
serv
atio
ns
(x 1
.0e7
)
Rob
ust
Sta
nd
ard
Dev
iati
on
Med
ian
Dif
fere
nce
Statistics of ΔTS for O&SI SAF and ACSPOMetop-A FRAC minus OSTIA
8 November 2010 SST Science Team Meeting 18
Pathfinder v5.0 (Day) - Reynolds SST
http://www.star.nesdis.noaa.gov/sod/sst/squam/PF/
Reynolds OISST uses Pathfinder as input. Still, the two products may differ by several tenths K
8 November 2010 SST Science Team Meeting 19
“Pathfinder v5.0 (Day) - OISST” vs. Wind SpeedPla
tform
sYear
Wind Speed (ms-1)
NOAA-17 mid-morning platform – Diurnal warming suppressed
http://www.star.nesdis.noaa.gov/sod/sst/squam/PF/
L2-L4 statistics for various L2s(L4 = OSTIA)
SST systems
* +Attributes
8 November 2010 20SST Science Team Meeting
Red: DayBlue: Night
Avg. num. of retrievals/24hr
Avg. Median Diff. (K)
Avg. Std Dev (K)
Robust Conv.
NESDIS MUT 73,00054,000
0.25-0.02
0.430.28
0.570.42
NAVO SEATEMP 163,000153,000
0.230.06
0.400.30
0.530.37
ACSPO GAC 2,500,0002,200,000
0.13-0.03
0.500.34
0.570.40
Pathfinder v5(L3P)
2,700,000(N_L2: 6,060,000)
1,843,000(N_L2: 4,100,000)
0.12-0.07
0.450.47
0.540.52
ACSPO FRAC 42,500,00044,500,000
0.140.04
0.450.33
0.590.47
O&SI SAF FRAC 42,900,00037,000,000
0.140.06
0.470.33
0.630.48
+ Average NOAA-18 is shown. Outliers not removed
SST systems
* +Attributes
8 November 2010 21SST Science Team Meeting
Red: DayBlue: Night
Avg. num. of retrievals/24hr
Avg. Median Diff. (K)
Avg. Std Dev (K)
Robust Conv.
NESDIS MUT 73,00054,000
0.22-0.05
0.430.37
0.530.49
NAVO SEATEMP 163,000153,000
0.220.04
0.380.33
0.47**0.39**
ACSPO GAC 2,500,0002,200,000
0.11-0.06
0.490.42
0.550.47
Pathfinder v5(L3P)
2,700,000(N_L2: 6,060,000)
1,843,000(N_L2: 4,100,000)
0.11-0.10
0.480.48
0.540.54
ACSPO FRAC 42,500,00044,500,000
0.160.05
0.460.40
0.550.52
O&SI SAF FRAC 42,900,00037,000,000
0.190.06
0.520.45
0.670.59
L2-L4 statistics for various L2s(L4 = Reynolds “AVHRR”)
+ Average NOAA-18 is shown. Outliers not removed **NB: 2006-pr OISST uses NAVO SEATEMP as input
8 November 2010 SST Science Team Meeting 22
Observations from validation against global L4 SSTs
Choice of L4 affects Mean and Std Dev statistics of L2-L4
Absolute values are L4-specific.
However, relative performance of L2 products can be
evaluated using (L2-L4) analyses, with any L4.
Main advantage of L2 vs. L4: Product performance is
monitored in near real time, using a global instantaneous view.
Work in progress
Add MODIS and VIIRS SSTs to SQUAM.
Sensitivity to reference L4 calls for “L4 vs. L4” evaluation.
Although beyond our initial plans, our NCEP RTG
colleagues suggested adding L4 comparisons to SST Quality
Monitor.
L4 vs. L4
Cross-evaluation of various L4s
238 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 24
Contribution to GHRSST Inter-Comparison Technical Advisory Group
http://www.star.nesdis.noaa.gov/sod/sst/squam/L4/
“OSTIA – GMPE” mean zonal difference
8 November 2010 SST Science Team Meeting 25
Year
Latitude
“L4s – GMPE”: time series statistics
8 November 2010 SST Science Team Meeting 26
More time-series at: www.star.nesdis.noaa.gov/sod/sst/squam/L4/l4_delsst_timeseries.htm
DOI_AVDOI_AARTG_HRRTG_LRGOESPOESOSTIACMC 0.2NAVO K10ODYSSEAGMPE
Reynolds OISST (AVHRR)Reynolds OISST (+ AMSR-E)Real Time Global high resolutionRTG low resolutionBlended POES and GOESOperational SST and Sea ice analysisCanadian Met. Centre 0.2 degreeNAVOCEANO 1/10 degreeMERSEA IFREMER/CERSATGHRSST Median Ensemble Product
Roughly, L4 products form 3 major groups:
DOI_AV, DOI_AA, RTG_LR, NAVO K10
RTG_HR, GOES-POES blended (with seasonal variation between: RTG_HR, RTG_LR)
OSTIA, CMC, & GMPE*ODYSSEA: production temporarily halted
Mean
Year
Std
Dev
Year
wrt GHRSST GMPE wrt GHRSST GMPE
Match-up statistics in SQUAM for various daily L4 products wrt. GMPE
SST systems
* +Attributes
Type/resolutionInput
Avg. Median Diff. (K)
Avg. Std Dev(K)
*Robust Conv.
Reynolds (AVHRR) Bulk, 0.25°IR (PF till `05, then NAVO), & in situ
0.02 0.31 0.48
Reynolds (+AMSR-E) Bulk 0.25°AVHRR IR, AMSR-E MW, & in situ
0.04 0.33 0.47
RTG low resolution Bulk, 0.5°AVHRR IR, & in situ
-0.09 0.29 0.57
NAVO K10 Bulk, 0.1°AVHRR, VISSR, AMSR-E, JPL cli.
0.01 0.27 0.43
POESGOES blended Bulk, 0.1°AVHRR, GOES
-0.06 0.27 0.52
RTG high resolution Bulk, 1/12°AVHRR IR physical retr., & in situ
-0.06 0.27 0.57
OSTIAFoundation, 0.05°
IR: AVHRR, AATSR, SEVIRIMW: AMSR-E, TMI, SSMI ice, & in situ
0.0 0.17 0.31
CMCFoundation, 0.2°
IR: AVHRR, AATSRMW: AMSR-E, & in situ & CMC sea/ice
-0.02 0.15 0.31
ODYSSEASubskin, 0.1°
IR: AATSR, AVHRR, VISSR, SEVIRI, MW: AMSR-E, TMI
-0.03 0.29 0.40
8 November 2010 27SST Science Team Meeting*robust parameters are resistant to outliers, may hide local issues. Should be used with additional diagnostics
8 November 2010 SST Science Team Meeting 28
Conclusion to L4 vs. L4 Comparisons
Currently, nine L4 daily products are continuously monitored in
SQUAM, wrt. each other.
Foundation SST products (OSTIA, CMC) appear more stable in
time, less noisy in space, and more consistent with satellite data.
G1SST is being evaluated (G1SST). RSS MW is in pipeline.
Future plans…
Validate all L4 SSTs against independently QCed in situ data (iQUAM).
Explore DV model. This should reduce cross-platform biases and spurious
noise in “L2-L4”, and will help to globally validate the DV model.
Cooperate with L4 producers to add missing L4s
Radiances
Monitoring Clear-Sky Radiances
298 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 30
Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS)
Web-Based NRT tool to monitor M-O bias- M (Model) = Community Radiative Transfer Model (CRTM) used in
ACSPO to simulate TOA Brightness Temperatures.
- O (Observation) = AVHRR Clear-Sky BTs in Ch3B, 4 & 5.
Key objectives- Fully understand and reconcile CRTM and AVHRR BTs
- Minimize cross-platform biases -
Users/Applications- Test and improve ACSPO products
- Validate and improve CRTM performance
- Contribute to sensor characterization and inter-calibration within Global Space-based Inter-Calibration System (GSICS)
8 November 2010 SST Science Team Meeting 31
MICROS Overview
www.star.nesdis.noaa.gov/sod/sst/MICROS/
MICROS is end-to-end system
8 November 2010 SST Science Team Meeting 32
M-O Biasesand Double-Differences
Warm M-O biases are due to a combined effect of incomplete model (aerosols not included; bulk SST used instead of skin; daily mean Reynolds SST is used to represent nighttime SST) and biased satellite sensor radiances (residual cloud).
Double differences (DDs) cancel out many possible systematic errors in CRTM and its input (SST and GFS, missing aerosol, etc).
Non-zero DDs are mainly due to errors in sensor calibration and spectral response functions. Largest systematic errors are in N18 (Ch4) and N19 (all bands).
NOAA-16 is unstable in whole monitoring period.
8 November 2010 SST Science Team Meeting 33
The effect of CRTM input on M-O bias (Reynolds SST used as CRTM input)
μ and σ: median and RSD over time
Spurious variations found when Reynolds SST used as CRTM input.
8 November 2010 SST Science Team Meeting 34
The effect of reference SST on M-O bias (OSTIA SST used as CRTM input)
Spurious time variability reduced when OSTIA used as CRTM input.The Std Deviations are also dramatically reduced.
8 November 2010 SST Science Team Meeting 35
Conclusion to Monitoring Radiances
SST is an unresolved combination of 2-3 sensor bands. Monitoring
individual bands is needed to unscramble SST anomalies.
Web-based near-real time Monitoring of IR Clear-sky Radiances
over Oceans for SST (MICROS) established
http://www.star.nesdis.noaa.gov/sod/sst/micros/
Currently, three users groups actively use MICROS
- ACSPO SST developers
- CRTM developers
- Sensor calibration scientists
Future plans…
Minimize M-O biases through: Adding aerosol in CRTM; Improving
AVHRR sensor characterization; Improving CRTM accuracy
Conclusion
Community Consensus
SSTs & Radiances
368 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 37
Conclusion
Community consensus methodologies and tools for SST
evaluation and validation are needed
Prototypes have been established at NESDIS
- SST Quality Monitor (SQUAM) for L2 & L4 products
http://www.star.nesdis.noaa.gov/sod/sst/squam/
- In situ SST Quality Monitor (iQuam)
http://www.star.nesdis.noaa.gov/sod/sst/iquam/
Satellite radiances in individual sensor bands should be monitored
- Monitoring of IR Clear-sky Radiances over Oceans for SST
http://www.star.nesdis.noaa.gov/sod/sst/micros/
We are open to any suggestions to make SQUAM, iQuam,
and MICROS the “community tools”
Questions?
Thank you!
388 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 39
Back-Up slides
8 November 2010 SST Science Team Meeting 40
Std Dev of “In Situ – Daily Reynolds SST” stratified by
in situ data types
All SSTs are strongly contaminated by outliers (drifters affected most).
Effect of QC on NCEP GTS SST(in situ minus daily Reynolds)
Ships
Drifters
Tropical Moorings
Coastal Moorings
8 November 2010 SST Science Team Meeting 41
Percent of in situ data excluded by QC
Percent of outliers in drifter SSTs is largest–
QC is needed most.
Percent of NCEP GTS dataexcluded by QC
Ships
Drifters
Tropical Moorings
Coastal Moorings
8 November 2010 SST Science Team Meeting 42
Pathfinder v5.0 (Night) - Reynolds SST
http://www.star.nesdis.noaa.gov/sod/sst/squam/PF/
Pathfinder v5 was recently added to SQUAM
8 November 2010 SST Science Team Meeting 43
Pathfinder v5.0 (Day) - Reynolds SST
http://www.star.nesdis.noaa.gov/sod/sst/squam/PF/
Pathfinder v5 was recently added to SQUAM